No abstract

Fine particulate matter (PM 2.5 ) is the major air pollutant in Beijing, posing serious threats to human health. Land use regression (LUR) has been widely used in predicting spatiotemporal variation of ambient air-pollutant concentrations, though restricted to the European and North American context. We aimed to estimate spatiotemporal variations of PM 2.5 by building separate LUR models in Beijing. Hourly routine PM 2.5 measurements were collected at 35 sites from 4th March 2013 to 5th March 2014. Seventy-seven predictor variables were generated in GIS, including street network, land cover, population density, catering services distribution, bus stop density, intersection density, and others. Eight LUR models were developed on annual, seasonal, peak/non-peak, and incremental concentration subsets. The annual mean concentration across all sites is 90.7 μg/m 3 (SD=13.7). PM 2.5 shows more temporal variation than spatial variation, indicating the necessity of building different models to capture spatiotemporal trends. The adjusted R 2 of these models range between 0.43 and 0.65. Most LUR models are driven by significant predictors including major road length, vegetation, and water land use. Annual outdoor exposure in Beijing is as high as 96.5 μg/m 3 . This is among the first LUR studies implemented in a seriously air-polluted Chinese context, which generally produce acceptable results and reliable spatial air-pollution maps. Apart from the models for winter and incremental concentration, LUR models are driven by similar variables, suggesting that the spatial variations of PM 2.5 remain steady for most of the time. Temporal variations are explained by the intercepts, and spatial variations in the measurements determine the strength of variable coefficients in our models.

No abstract

Nitrogen (N) enrichment has been reported to affect the soil bacteria community in natural temperate grasslands. However, it remains unknown how the bacteria community responds to N enrichment in degraded grasslands. Here, we established multi-level N enrichment experiments in temperate grasslands under non-degraded (ND), moderately degraded (MD), severely degraded (SD), and extremely degraded (ED) sites in northern China. The bacteria community was investigated by highthroughput sequencing and linked to major abiotic and biotic factors. We found bacterial diversity was lower in ED grassland than the other grasslands, and community composition highly varied across the four degrees of degradation. Change in bacterial diversity was due to the different variations in dominant phyla, and soil phosphorus content contributed to the variation in community composition across grasslands under increasing degradation. In ND, MD, and SD grasslands, bacterial diversity was not significantly altered by N enrichment below 30 g-N m −2 yr −1 but declined when N enrichment was greater than 30 g-N m −2 yr −1 . The bacterial diversity loss was associated with the decreased soil pH under N enrichment. However, in ED grassland, bacterial diversity decreased when N enrichment was below 30 g-N m −2 yr −1 and remained unchanged when N enrichment was greater than 30 g-N m −2 yr −1 . Change in bacterial diversity was modulated by soil N availability. Besides, N enrichment shifted bacterial community composition via changing soil N availability. Our study identified bacterial diversity loss in ED grassland and differently nonlinear responses of bacterial diversity to multi-level N enrichment in grasslands under different degrees of degradation.

Vegetation in urban settings is heavily altered by anthropogenic impacts. However, the impacts of urbanization on vegetation are not well understood. Here, we quantified the impacts of urbanization on vegetation in 48 Chinese coastal cities and explored their dynamic characteristics from 1990 to 2015. The indirect impacts of urbanization on vegetation at different spatial and temporal scales were also determined. Remote-sensing-based results indicated that vegetation conditions decreased significantly as the proportion of built-up land increased. However, the difference between the observed decline trend and the theoretical one means that urbanization in most coastal areas promoted vegetation growth. Except vegetation loss from land changes, there had been positive indirect effects of urbanization on vegetation conditions at several scales in coastal areas across the study period. These positive indirect impacts are attributed to the balances between vegetation restoration and management, the deterioration of plants’ living conditions, and urban microclimate. Due to Chinese environmental actions over 25 years, the number of cities with a positive indirect impact increased. Our study might enhance the systematic understanding of the response of vegetation to urbanization in China.